Since my PhD years, I have been focusing on the interaction of financial and operational decisions in supply chains, including
1. Trade Credit and Supply Chain Finance
2. Managing operations under financial constraints
3. FinTech and Financial Innovation
Recently, I have been working on operations and governance issues related to digital technologies, including innovations of platform governance and operations (below is a video explaining my recent work on crowd-judging), blockchain, and artificial intelligence.
My other research interests include value chain management and innovation, risk management, and business analytics.
Selected Working Papers
Generative AI and Copyright: A Dynamic Perspective
with Angela Huyue Zhang
Abstract
The rapid advancement of generative AI is poised to disrupt the creative industry. Amidst the immense excitement for this new technology, its future development and applications in the creative industry hinge crucially upon two copyright issues: 1) the compensation to creators whose content has been used to train generative AI models (the fair use standard); and 2) the eligibility of AI-generated content for copyright protection (AI-copyrightability). While both issues have ignited heated debates among academics and practitioners, most analysis has focused on their challenges posed to existing copyright doctrines. In this paper, we aim to better understand the economic implications of these two regulatory issues and their interactions. By constructing a dynamic model with endogenous content creation and AI model development, we unravel the impacts of the fair use standard and AI-copyrightability on AI development, AI company profit, creators income, and consumer welfare, and how these impacts are influenced by various economic and operational factors. For example, while generous fair use (no compensation to creators for data used for AI training) benefits all parties when abundant training data exists, it could hurt creators and consumers when such data is scarce. Similarly, stronger AI-copyrightability (AI content enjoys more copyright protection) could hinder AI development, and reduce social welfare. Our analysis also highlights the complex interplay between these two copyright issues. For instance, when existing training data is scarce, generous fair use may be preferred only when AI-copyrightability is weak. Our findings underscore the need for policymakers to embrace a dynamic, context-specific approach in making regulatory decisions and provide insights for business leaders navigating the complexities of global regulatory environment.
Capacity Expansion in Service Platforms: Ownership, Commitment, and Flexibility
with Heikki Peura
Abstract:
Service platforms connect consumers to independent providers who typically deliver the service using their own assets (e.g., ride-hailing with suitable cars). Platforms expanding their services have trialled programs to attract prospective providers who do not yet possess the requisite assets. These programs diverge in terms of asset ownership and contract terms. Platform financing seeks to improve upon conventional bank loans, with new providers investing in assets using loans from the platform instead. Under employment and rental, by contrast, the platform invests in assets and offers them to providers via either long-term employment-like or short-term rental contracts. This paper develops a game-theoretical model to examine the viability and relative performance of these mechanisms. With bank financing as a benchmark, we find that each mechanism can be profitable, but suffers from potential pitfalls. For example, unlike comparable supply-chain finance schemes, platform financing often fails to benefit the platform in simple interest-only form and instead requires payments tied to providers' on-platform performance. Comparing the mechanisms highlights a trade-off between the platform committing to a mutually beneficial contract with the providers and exploiting their flexibility as independent service providers. As a result, the platform offers the semi-flexible financing option when investment costs and demand are low, commits to employment when demand increases, and otherwise offers the most flexible rental option. Further, we find that minimum-wage regulation could benefit both not only service providers but also a growing platform, especially under financing; and stronger network effect further benefits employment.
Bargaining, Operational Investment, and Trade Credit
with Leon Yang Chu and Jin Yao
Abstract:
Trade credit is widely used in transactions between firms who are financially unconstrained. In this paper, we propose a novel theory of trade credit to rationalize this phenomenon: to alter the dynamics in the negotiation process and result in a distribution of payoffs between supply chain partners that induces more efficient operational investment. We construct a bilateral supply chain model where a supplier and a retailer, neither financially constrained, interact over multiple periods. In each period, the buyer first makes a non-contractable operational investment that could boost market demand, and then the two parties negotiate over the contract terms via an alternating-offer bargaining process (Rubinstein 1982). We consider two types of contracts: 1) cash-only (the two parties bargain over the amount of cash payment); 2) trade credit (the two parties bargain over the amount of cash payment and trade credit payment; the latter paid by the retailer to the supplier in the next period). Our analysis reveals that in the dynamic bargaining process, outstanding trade credit owed by the retailer to the supplier increases the share of market revenue that the retailer could keep, inducing the retailer to invest more. As such, the profits for both the retailer and supplier are greater under the equilibrium trade credit contract than those under the optimal cash-only contract, creating a win-win situation. Further, we uncover how different factors influence the usage and benefit of trade credit in its bargaining role. For example, we find that more trade credit is used when demand is more time-sensitive demand and the interest rates (faced by both firms) are low. By identifying a new role of trade credit, our findings provide insights to managers on what factors to take into account when negotiating contractual terms. Our paper also contributes to multiple streams of academic literature by establishing trade credit as a mechanism to alleviate holdup problems in a dynamic bargaining setting.
Financial Pooling in a Supply Chain
with Ming Hu, Jingchen Liu, and Alex Qu Qian
Abstract:
Trade credit is often extended by suppliers to buyers who often have easier access to external financing. Moreover, many buyers also delay paying their suppliers beyond the agreed due day. Prior literature attributes this phenomenon to quality assurance or buyer's abuse of market power. In this paper, we show that pooling could be another reason behind this practice. Using a game-theoretic model that explicitly captures the liquidity shocks faced by different supply chain partners, we analyze the total financing cost of the supply chain under endogenous supply contract and working capital policies. We show that the embedded stretching option of trade credit allows supply chain partners to pool their liquidity buffers. Due to this pooling effect, even if the supplier's financing costs are strictly higher than the buyer's, the buyer may still demand trade credit from the supplier in order to lower the total financing cost. The model reveals that trade credit is more efficient than cash on delivery when the supplier's cost for collecting trade credit is low (e.g., when the retailer trusts the supplier) or when the supplier does not have access to a low-cost financing channel when facing liquidity shocks. This pooling effect also dictates that variabilities of firms' liquidity shocks have asymmetric impact on the efficiency of trade credit: while trade credit can only be more efficient than cash on delivery when the supplier's liquidity shock has a sufficiently large variability, it could benefit the supply chain even when the buyer's liquidity shock is deterministic (e.g., an investment opportunity). The benefit of financial pooling increases as the buyer's supplier portfolio becomes more diversified. As an innovative financing scheme, reverse factoring further enhances the efficiency of this pooling effect and, as a result, reduces the overall supply chain financing cost.
Recently Accepted Papers
Crowd-judging on Two-sided Platforms: An Analysis of In-group Bias
with Alan P. Kwan and Angela Huyue Zhang, Management Science, forthcoming
-- Best Paper Award, the 15th International Conference for CSAMSE, 2023
-- Featured in MIT Technology Review
Abstract
Disputes over transactions on two-sided platforms are common and are usually arbitrated through platforms’ customer service departments or third-party service providers. In this paper, we study crowd-judging, a novel crowd-sourcing mechanism whereby users (buyers and sellers) volunteer as jurors to decide disputes arising from the platform. Using a rich dataset from the dispute resolution center at Taobao, a leading Chinese e-commerce platform, this paper aims to understand this innovation and propose and analyze potential operational improvements. We focus on in-group bias (buyer jurors favor the buyer, likewise for sellers). Platform users, especially sellers, share the perception that in-group bias is prevalent and thus systematically sways case outcomes given the majority of users on such platforms are buyers, undermining the legitimacy of crowd-judging.
Our empirical findings suggest that such concern is not completely unfounded: on average, a seller juror is approximately 10% likelier to vote for a seller. Such bias is 30% higher among cases that are less clear-cut and decided by a thin margin, and is aggravated when jurors perceive that their in-group's interests are threatened. However, the bias diminishes as jurors gain experience: a user's bias reduces by 95% as their experience grows from zero to the sample-median level. Combining these findings with a simulation that incorporate juror participation dynamics, we estimate that in-group bias influences the outcomes of no more than 2% of cases, providing some assurance about judging quality. In addition, we find that more dynamic case allocation policies could outperform simply increasing panel size both in terms of reducing in-group bias and nurturing a more sustainable juror pool. We also caution that aggressively recruiting new jurors or providing feedback to jurors may amplify bias.
Advance Selling to Ease Financial Distress
with Yiangos Papanastasiou and Shuang Xiao, Management Science, forthcoming
Abstract
Left unable to provide service during the COVID-19 pandemic, many small businesses have experimented with alternative ways of generating income. One approach that has gained traction is the use of advance selling, whereby the firm asks consumers in its local community to support the business by paying in advance for consumption at a future date. In this paper, we develop a game theoretic model to investigate whether and how advance selling schemes can be successfully implemented by firms facing financial distress. In cases of high distress (i.e., where obtaining bank financing is infeasible given the firm's financial need), we show that advance selling in its classic implementation can help the firm secure its survival in some scenarios, but may suffer from significant inefficiencies associated with strategic consumer behavior and firm moral hazard. We demonstrate that two modifications of the classic scheme currently observed in practice---namely, (i) the introduction of an "all-or-nothing" clause, and (ii) selling future discount coupons as opposed to the full service---can expand the set of scenarios in which survival is ensured, while also allowing the firm to extract higher profit. In cases of moderate financial distress (i.e., where bank financing is a feasible but inefficient option), we find that simple advance selling schemes typically fail to make an impact. However, we show that a more complex scheme, combining both of the aforementioned modifications simultaneously, can be used in conjunction with bank financing to generate a substantial improvement in firm profit.
Improving Dispute Resolution in Two-sided Platforms: The Case of Review Blackmail
with Yiangos Papanastasiou and Angela Huyue Zhang, Management Science, 69(10), 6021-6037
Abstract
We study the relative merits of different dispute resolution mechanisms in two-sided platforms, in the context of disputes involving malicious reviews and blackmail. We develop a game-theoretic model of the strategic interactions between a seller and a (potentially malicious) consumer. In our model, the seller takes into account the impact of consumer reviews on his future earnings; recognizing this, a malicious consumer may attempt to blackmail the seller by purchasing the product, posting a negative review, and demanding ransom to remove it. Without a dispute resolution mechanism in place, the presence of malicious consumers in the market can lead to a significant decrease in seller profit, especially in settings characterized by high uncertainty about product quality. The introduction of a standard centralized dispute resolution mechanism (whereby the seller can report allegedly malicious reviews to the host platform, which then judges whether to remove the review) can restore efficiency to some extent, but requires the platform's judgments to be both very quick and highly accurate. We demonstrate that a more decentralized mechanism (whereby the firm is allowed to remove reviews without consulting the platform, subject to ex post penalties for wrongdoing) can be much more effective, while simultaneously alleviating -- almost entirely -- the need for the platform's judgments to be quick. Our results suggest that decentralization, when implemented correctly, may represent a more efficient approach to dispute resolution.
Publications
Dynamic Trade Finance in the Presence of Information Friction and FinTech
with Hau L. Lee, Christopher S. Tang, and Yuxuan Zhang, Manufacturing & Service Operations Management, 25(6), 2038-2055
-- Best Paper Award, The International Conference on Smart Finance, 2021
-- Best Paper Award (Third Place), Institute of Supply Chain and Operations Management Annual Meeting, 2021
Platform Tokenization: Financing, Governance, and Moral Hazard
with Jiri Chod and Nikolaos Trichakis, Management Science, 68(9), 6411-6433
-- Featured at Management Science Review Blog
-- Finalist, MSOM iFORM SIG Best Paper Competition, 2023